A bandwidth-efficient high-performance RTL-microarchitecture of 2D-convolution for deep neural networks

This paper presents an RTL (Register Transfer Logic) level microarchitecture of hardware-and bandwidth-efficient high-performance 2D convolution unit for CNN in deep learning. The 2D convolution unit is made up of three main components including a dedicated Loader, a Circle Buffer, and a MAC (Multiplier-Accumulator) unit.